Efficiency of DNA Mini-Barcoding to Assess Mislabeling in Commercial

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Article Efﬁciency of DNA Mini-Barcoding to Assess Mislabeling in Commercial Fish Products in Italy: An Overview of the Last Decade

Laura Filonzi, Marina Vaghi, Alessia Ardenghi, Pietro Maria Rontani, Andrea Voccia and Francesco Nonnis Marzano *

Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Viale delle Scienze 11, 43124 Parma, Italy; laura.ﬁ[email protected] (L.F.); [email protected] (M.V.); [email protected] (A.A.); [email protected] (P.M.R.); [email protected] (A.V.) * Correspondence: [email protected]; Tel.: +39-0521-905643

Abstract: The problem of fish traceability in processed products is still an important issue in food safety. Major attention is nowadays dedicated to consumer health and prevention of possible frauds regulated by national and international laws. For this reason, a technical approach is fundamental in revealing mislabeling at different levels. In particular, the use of genetic markers has been standardized and DNA barcoding is considered the gold-standard strategy to examine and prevent species substitution. Considering the richness of available DNA databases, it is nowadays possible to rapidly reach a reliable taxonomy at the species level. Among different approaches, an innovative method based on DNA mini barcoding has recently been proposed at an international level. Starting from this evidence, we herein illustrate an investigation dealing with the evolution of this topic in Italy over the last decade. The molecular analysis of 71 commercial fish samples based on mini-COI Citation: Filonzi, L.; Vaghi, M.; sequencing with two different primer sets reached an amplification success rate of 87.3 and 97.2%. Ardenghi, A.; Rontani, P.M.; Voccia, The investigation revealed four major frauds (5.8%) and four minor ones (5.8%). Results highlighted A.; Nonnis Marzano, F. Efficiency of a decrease in incorrect labeling in Italy from 32% to 11.6% over the last decade, although a recurrent DNA Mini-Barcoding to Assess involvement of “endangered” species sensu IUCN was still observed. Mislabeling in Commercial Fish Products in Italy: An Overview of the Last Decade. Foods 2021, 10, 1449. Keywords: food frauds; conservation; molecular genetics; mitochondrial DNA; cytochrome oxi- https://doi.org/10.3390/foods10071449 dase; biodiversity

Academic Editor: Tiziana Pepe

Received: 10 May 2021 1. Introduction Accepted: 15 June 2021 The consumption of seafood products has increased all over the world during the Published: 22 June 2021 last 50 years as demonstrated by data issued by the United Nations Food and Agriculture Organization (FAO) [1,2] that estimated the value of fish commerce to be over hundreds of Publisher’s Note: MDPI stays neutral billion dollars each year. Considering the importance of fish trade in the globalization era, with regard to jurisdictional claims in consistent monitoring of the production chain focusing on technological developments, published maps and institutional affil- handling, processing and distribution by global networks is, therefore, necessary [3]. iations. Nowadays, food quality and safety issues are crucial points for consumers, also considering the frequency of fish species substitutions. Basic consequences may be health problems that occur primarily through the consumption of cryptic species coming from contaminated areas or able to trigger allergy problems [4]. Despite financial fraud still being the main Copyright: © 2021 by the authors. issue [5], major attention must be dedicated to such cryptic species as those belonging to Licensee MDPI, Basel, Switzerland. the genera Pangasius, Salmo and Tilapia whose aquaculture exploitation makes them easy This article is an open access article substitutes for wild species [4]. distributed under the terms and Precautionary measures are, therefore, necessary, particularly for products that are conditions of the Creative Commons not visually recognizable at sight and are indistinguishable on a morphological basis after Attribution (CC BY) license (https:// processing. Deliberate mislabeling and replacement of high-value species with cheaper creativecommons.org/licenses/by/ ones is an Economically Motivated Adulteration (EMA) and is considered as fraud [5]. In a 4.0/).

Foods 2021, 10, 1449. https://doi.org/10.3390/foods10071449 https://www.mdpi.com/journal/foods Foods 2021, 10, 1449 2 of 11

report paper published by the European Parliament in 2013, seafood was identified as the second most likely group of food to be subject to fraud, following olive oil [6]. Although the European Union labeling law (EU Regulation No. 1379/2013) [7] re- quests appropriate species traceability and labeling (scientific binomial nomenclature based on genus and species together with the common name), the identification of processed species is often difficult. Many scientists are working with innovative technologies to assess taxa identification and authenticity. Several molecular methods have been proposed to identify the correct species, from the use of single-protein or species-specific DNA sequences to modern genomic approaches. Among the wide variety of DNA methods nowadays available, the choice is mainly influenced by use simplicity and affordable costs in relation to the product value [8]. In recent years, the gold-standard strategy to examine and prevent species fraud has been DNA barcoding, a fast and cost-effective method for correct classification at a species level [9]. The original approach is based on the sequence analysis of a 650-bp mitochondrial DNA fragment. The cytochrome c oxidase I (COI) gene is the favorite sequence to act as a “barcode” to identify and delineate the animal lifeform [10]. Although the analysis of long DNA fragments is complex due to degradation along the different steps from production to analysis, most of the mtDNA-based studies have analyzed the full-length COI barcode [11,12]. Since the first applications of mitochondrial DNA barcoding [13], and then through constant methodological improvements [14], the most recent advances have led to an innovative approach based on mini-barcodes [15–17]. The methodology refers to the analysis of short DNA fragments and it can be applied in different fields of systematics (from museum collection research to forensic applications). COI mini-barcoding is, therefore, useful to assess the correct taxonomy in processed products. This is particularly the case with commercial fish, for which the correct preservation under stable refrigerated conditions is a major issue during fishing, transportation and distribution. In addition, fish processing for preservation is the major cause of DNA degradation. Consequently, molecular analyses to reveal species substitution may face DNA degradation limitations and, therefore, become biased by technical questions. The possi- bility of analyzing short DNA fragments such as COI mini-barcoding seems to solve this issue. In the field of ichthyology, the application of mini-barcoding is nowadays possible thanks to the availability of specific databases accounting for millions of COI sequences. To give a general idea, BOLD database reports cover more than 24,000 barcoded species among Actinopterygii and Elasmobranchii. On the other hand, it is noteworthy to observe that data redundancy may generate confusion or technical biases due to contradictory attribution within a genus level. Starting from past experience of the application of COI and CytB barcoding, besides the use of additional markers [18], for the identification of species substitution in fish products [19], a new investigation was carried out to verify the usefulness of COI mini- barcoding as an innovative methodology to substitute for classic barcoding. The research was focused on sampling and analyzing the same taxa purchased in the same department stores to assess the evolution of cryptic species mislabeling after a decade, also considering the application of new European regulations [7]. The suitability of COI mini-barcoding and the evolution of the mislabeling issue are herein discussed, also considering some critical ecological, taxonomic and commercial aspects that have been arisen by experts based on their judgments.

2. Materials and Methods Fresh and frozen commercial ﬁsh products were acquired in 10 different department stores located in the Emilia Romagna region during 2020 and 2021. The different department stores belonged to the major brands fully distributed over the entire country, with their own national ﬁsh provider. In this way, although executed locally, the research had national coverage. Foods 2021, 10, 1449 3 of 11

A small sample of the edible tissue of approximately 50 mg was collected and fixed in absolute ethanol under refrigerated conditions. Samples were stored at −20 ◦C to be processed within one week of purchasing. A total number of 71 specimens belonging to 27 putative seawater species were analyzed. The samples dataset was prepared, listing the declared names and areas of fishing. The entire dataset is reported in Table1. It is noteworthy to observe that four samples (MB43, MB64, MB66, MB71) did not report the origin in the label either as a specific FAO fishing area or a summary geographic declared one.

Table 1. Detailed description of analyzed samples and information reported in the labels (common name, declared scientiﬁc name and ﬁshing area). “N/A” (not available) refers to lacking label information.

Sample ID Geographical Origin Common Name Declared Scientific Name MB01 Southeast Atlantic Ocean Deep-water Cape hake Merluccius capensis e/o M. paradoxus MB02 Northeast Atlantic Ocean Pink salmon Oncorhynchus gorbuscha MB03 Northeast Atlantic Ocean—Iceland seabed Atlantic cod Gadus morhua MB04 East Central Atlantic Ocean Goldblotch grouper Epinephelus costae MB05 Northeast Atlantic Ocean Pink salmon Oncorhynchus gorbuscha MB06 Eastern Indian Ocean Swordfish Xiphias gladius MB07 East Central Atlantic Ocean Angolan dentex Dentex angolensis MB08 Northeast Atlantic Ocean—Baltic Sea Atlantic cod Gadus morhua MB09 Northeast Pacific Ocean Pink salmon Oncorhynchus gorbuscha MB10 Northeast Atlantic Ocean—Baltic Sea Atlantic cod Gadus morhua MB11 Southeast Atlantic Ocean Blue shark Prionace glauca MB12 Northeast Atlantic Ocean Haddock Melanogrammus aeglefinus MB13 Northeast Pacific Ocean Pink salmon Oncorhynchus gorbuscha MB14 East Central Atlantic Ocean Goldblotch grouper Epinephelus costae MB15 Northeast Atlantic Ocean Haddock Melanogrammus aeglefinus MB16 Southeast Atlantic Ocean Deep-water Cape hake Merluccius capensis e/o M. paradoxus MB17 Northeast Atlantic Ocean—Iceland seabed Atlantic cod Gadus morhua MB18 Southeast Atlantic Ocean Deep-water Cape hake Merluccius capensis e/o M. paradoxus MB19 Central Western Pacific Ocean Skipjack tuna Katsuwonus pelamis MB20 East Central Atlantic Ocean Angolan dentex Dentex angolensis MB21 Pacific Ocean Northeast or North West Pink salmon Oncorhynchus gorbuscha MB22 Northwest Atlantic Ocean Atlantic cod Gadus morhua MB23 Northeast Pacific Ocean North Pacific hake Merluccius productus MB24 Southeast Atlantic Ocean Swordfish Xiphias gladius MB25 Central Western Pacific Ocean Skipjack tuna Katsuwonus pelamis MB26 Northeast Pacific Ocean North Pacific hake Merluccius productus MB27 Northeast Atlantic Ocean—Iceland seabed Atlantic cod Gadus morhua MB28 East Central Atlantic Ocean Angolan dentex N/A MB29 Northeast Atlantic Ocean Beaked redfish N/A MB30 Pacific Ocean Northeast or North West Alaska pollock Theragra chalcogramma MB31 Northeast Atlantic Ocean Atlantic cod Gadus morhua MB32 Pacific Ocean Northeast or North West Pink salmon Oncorhynchus gorbuscha MB33 Pacific Ocean Northeast or North West Alaska pollock Theragra chalcogramma MB34 Central or Southeast Pacific Ocean Swordfish Xiphias gladius MB35 Southeast Atlantic Ocean Blue shark Prionace glauca MB36 Southeast Atlantic Ocean Swordfish Xiphias gladius MB37 Atlantic Ocean Beaked redfish Sebastes norvegicus MB38 Northeast Atlantic Ocean Tub gurnard Chelidonichtys lucerna MB39 East Central Atlantic Ocean Spiny turbot Psettodes spp. MB40 East Central Atlantic Ocean Swordfish Xiphias gladius MB41 Western Mediterranean Leerfish Lichia amia MB42 Southeast Atlantic Ocean Deep-water Cape hake Merluccius capensis e/o M. paradoxus MB43 N/A Alaska pollock Theragra chalcogramma MB44 Northwest Atlantic Ocean Porbeagle Lamna nasus MB45 Northeast Atlantic Ocean European plaice Pleuronectes platessa MB46 Indian Ocean Yellowfin tuna Thunnus albacares MB47 Lake Victoria Nile perch Lates niloticus MB48 Northwest Atlantic Ocean Picked dogfish Squalus acanthias MB49 Northeast Atlantic Ocean Golden redfish Sebastes norvegicus MB50 East Central Atlantic Ocean Bearded brotula Brotula barbata MB51 Northeast Atlantic Ocean European plaice Pleuronectes platessa MB52 East Central Atlantic Ocean Shortfin mako Isurus oxyrinchus MB53 Lake Victoria, Tanzania Nile perch Lates niloticus MB54 East Central Atlantic Ocean Porbeagle Isurus oxyrinchus Foods 2021, 10, 1449 4 of 11

Table 1. Cont.

Sample ID Geographical Origin Common Name Declared Scientific Name MB55 North Sea Smooth-hound Mustelus mustelus MB56 Northwest Atlantic Ocean Halibut Reinhardtius hippoglossoides MB57 Unreported Alaska pollock Theragra chalcogramma MB58 Northeast Atlantic Ocean European plaice Pleuronectes platessa MB59 Iceland seabed Beaked redfish Sebastes mentella MB60 Norwegian Sea Saithe Pollachius virens MB61 Pacific Ocean Southwest Shortfin mako Isurus oxyrinchus MB62 Norwegian Sea Atlantic cod Gadus morhua MB63 Northeast Atlantic Ocean Saithe Pollachius virens MB64 N/A Swordfish Xiphias gladius MB65 Northeast Atlantic Ocean European plaice Pleuronectes platessa MB66 N/A Porbeagle N/A MB67 Northeast Atlantic Ocean Atlantic cod Gadus morhua MB68 North Sea Smooth-hound Mustelus mustelus MB69 Pacific Ocean Northwest Pacific cod Gadus macrocephalus MB70 Northeast Atlantic Ocean Atlantic cod Gadus morhua MB71 N/A Alaska pollock N/A

Genomic DNA was extracted and purified from about 10 mg of ethanol-preserved samples using the Wizard® Genomic DNA Purification Kit (Promega, Madison, WI, USA). Purified DNA was evaluated by means of 1% agarose gel electrophoresis. No samples were discharged due to bad DNA quality although some of them were considered borderline (as outlined in the Results section). Two different sets of primers were tested. The first pair of universal primers, Fish_miniFW: ATCACAAAGACATTGGCACCCT and Fish_miniRV: AATGAAGGGGGGAGGAGTCAGAA, specifically proposed by Sultana et al. [17] for fish species, were used and are herein named “Fish_Mini”. A 295 bp fragment of the mitochondrial COI gene was amplified through polymerase chain reaction (PCR) amplification using a Bio-Rad T100 Thermal Cycler. The cycling conditions were 95 ◦C for 10 min, followed by 34 cycles of 95 ◦C for 45 s, 57 ◦C for 45 s, 72 ◦C for 45 s and a final step at 72 ◦C for 10 min. The second set of primers was tested following the protocol suggested by Shokralla et al. [15]. Amplicons of 226 base pairs were obtained using a primer pair originally called Mini_SH-E. The two primers, “Fish_miniE”_F 50-CACGACGTTGTAAAACGACACYAAICAYAAAGAYATIGGC- AC-30 (forward) and Fish_miniE_R 50-GGATAACAATTTCACACAGGCTTATRTTRTTTATICGIG- GRAAIGC-30 (reverse), were chosen and are herein referred to as “Fish_miniE”. The PCR was set as follows: 34 cycles of 45 s at 95 ◦C, 45 s at 67 ◦C, and 45 s at 72 ◦C, after an initial 10 min denaturation step at 95 ◦C and a final extension at 72 ◦C for 10 min. The chemical conditions for both approaches were the following: a reaction volume of 20 µL—containing 1 U of GoTaq Polymerase (Promega, Madison, WI, USA), Mg2+ 1.5 mM, dNTPs 0.2 mM and 10 pmol of each primer—was used. Amplicons were separated by 2.5% agarose gel electrophoresis and purified using the Qiagen MinElute PCR Purification Kit. The quality of the purified sample (1 µL) was visualized in 1.5% agarose gel that yielded clear bands. DNA quantity was evaluated using the Qubit dsDNA HS (High Sensitivity) Assay Kit (Invitrogen, Waltham, MA, USA) with a Qubit 3.0 Fluorometer (Life Technologies, Waltham, MA, USA). COI sequencing of both amplified regions was performed by the MACROGEN Europe service (Amsterdam, The Netherlands). Twenty percent of the samples were locally reanalyzed using a CEQ8000 DNA Analysis System (Beckman Coulter, Milan, Italy) based on capillary electrophoresis. The analytical conditions are reported in detail in Filonzi et al. [19]. The obtained sequences were manually corrected using MEGA 7.0 [20] and compared with those available in the genomic databases of GenBank using the BLAST service and BOLD (Barcode of Life Data System). In both cases, the species level was assigned when the identity rate was greater than 98% considering either BLAST or BOLD analyses [21]. The accession numbers of selected reference sequences displaying the highest identity score are available on request. Foods 2021, 10, 1449 5 of 11

3. Results Data concerning 71 analyzed samples are reported in Table2. Considering the two different primer sets, “Fish_miniE” [15] successfully amplified 62 samples out of 71 (87.3% success rate) while “Fish_mini” [17] displayed a positive result in 69 of 71 samples (97.2%). In our dataset, four samples (MB28, MB29, MB66, MB71) did not have a clear scientific name (5.6%) and species comparison was executed based on common names. Similarly, four additional samples (MB43, MB64, MB66, MB71) did not report the origin on the label either as a specific FAO fishing area or a geographic declared region (5.6%).

Table 2. Scientiﬁc names and identity percentage values of each sample are provided both for BLAST and BOLD alignment analysis. Major frauds: mislabeling at genus level; minor frauds: different species within the same genus. Major species substitutions in bold; minor substitutions underlined; N/A: Not Available.

GenBank Result % Identity % Identity Sample ID Declared Scientific Name BOLD Result (BLAST) GenBank BOLD Merluccius capensis e/o M. MB01 Merluccius paradoxus 99.1 Merluccius paradoxus 98.9 paradoxus MB02 Oncorhynchus gorbuscha Oncorhynchus gorbuscha 98.3 Oncorhynchus gorbuscha 97.7 MB03 Gadus morhua Gadus morhua 98.6 Gadus morhua 98.4 MB04 Epinephelus costae Epinephelus costae 98.3 Epinephelus costae 99.1 MB05 Oncorhynchus gorbuscha Oncorhynchus gorbuscha 97.7 Oncorhynchus gorbuscha 98.0 MB06 Xiphias gladius Xiphias gladius 100 Xiphias gladius 100 MB07 Dentex angolensis Dentex maroccanus 99.1 Dentex macrophtalmus 100 MB08 Gadus morhua Gadus morhua 98.3 Gadus morhua 98.1 MB09 Oncorhynchus gorbuscha Oncorhynchus gorbuscha 98.6 Oncorhynchus gorbuscha 100 MB10 Gadus morhua Gadus morhua 98.3 Gadus morhua 98.0 MB11 Prionace glauca Prionace glauca 99.1 Prionace glauca 100 MB12 Melanogrammus aeglefinus Melanogrammus aeglefinus 99.1 Melanogrammus aeglefinus 100 MB13 Oncorhynchus gorbuscha Oncorhynchus gorbuscha 99.5 Oncorhynchus gorbuscha 100 MB14 Epinephelus costae Epinephelus costae 98.2 Epinephelus costae 99.1 MB15 Melanogrammus aeglefinus Melanogrammus aeglefinus 99.5 Melanogrammus aeglefinus 100 Merluccius capensis e/o M. MB16 Merluccius paradoxus 98.2 Merluccius paradoxus 99.1 paradoxus MB17 Gadus morhua Gadus morhua 98.2 Gadus morhua 100 Merluccius capensis e/o M. MB18 Merluccius paradoxus 100 Merluccius paradoxus 100 paradoxus MB19 Katsuwonus pelamis Thunnus thynnus 98.7 Thunnus maccoyii 100 MB20 Dentex angolensis Dentex maroccanus 96.9 Dentex macrophtalmus 99.4 MB21 Oncorhynchus gorbuscha Oncorhynchus gorbuscha 98.8 Oncorhynchus gorbuscha 100 MB22 Gadus morhua Gadus morhua 99.1 Gadus morhua 98.7 MB23 Merluccius productus Merluccius productus 98.8 Merluccius productus 100 MB24 Xiphias gladius Xiphias gladius 98.7 Xiphias gladius 100 MB25 Katsuwonus pelamis Thunnus thynnus 99.2 Thunnus maccoyii 100 MB26 Merluccius productus Merluccius productus 99.1 Merluccius productus 100 MB27 Gadus morhua Gadus morhua 99.1 Gadus morhua 100 MB28 N/A Dentex angolenses 99.1 Dentex angolenses 100 MB29 N/A Sebastes mentella 99.1 Sebastes mentella 99.5 Foods 2021, 10, 1449 6 of 11

Table 2. Cont.

GenBank Result % Identity % Identity Sample ID Declared Scientiﬁc Name BOLD Result (BLAST) GenBank BOLD MB30 Theragra chalcogramma Theragra chalcogramma 99.5 Gadus chalcogrammus 100 MB31 Gadus morhua Gadus morhua 99.4 Gadus morhua 98.8 MB32 Oncorhynchus gorbuscha Oncorhynchus gorbuscha 99.5 Oncorhynchus gorbuscha 100 MB33 Theragra chalcogramma Theragra chalcogramma 99.5 Gadus chalcogrammus 100 MB34 Xiphias gladius Xiphias gladius 99.5 Xiphias gladius 100 MB35 Prionace glauca Prionace glauca 99.5 Prionace glauca 99.4 MB36 Xiphias gladius Xiphias gladius 100 Xiphias gladius 100 MB37 Sebastes norvegicus Sebastes norvegicus 99.1 Sebastes viviparus 100 MB38 Chelidonichtys lucerna Merluccius paradoxus 98.7 Merluccius paradoxus 99.1 MB39 Psettodes spp. Psettodes bennettii 99.1 Psettodes bennettii 99.5 MB40 Xiphias gladius Xiphias gladius 100 Xiphias gladius 100 MB41 Lichia amia Lichia amia 99.1 Lichia amia 99.0 Merluccius capensis e/o M. MB42 Merluccius paradoxus 99.1 Merluccius paradoxus 98.1 paradoxus MB43 Theragra chalcogramma Theragra chalcogramma 99.1 Gadus chalcogrammus 100 MB44 Lamna nasus Isurus oxyrinchus 99.5 Isurus oxyrinchus 99.5 MB45 Pleuronectes platessa Pleuronectes platessa 100 Pleuronectes platessa 99.1 MB46 Thunnus albacares Thunnus albacares 99.6 Thunnus albacares 99.1 MB47 Lates niloticus Lates niloticus 100 Lates niloticus 100 MB48 Squalus acanthias Squalus acanthias 99.1 Squalus acanthias 98.2 MB49 Sebastes norvegicus Sebastes norvegicus 99.1 Sebastes viviparus 99.5 MB50 Brotula barbata Brotula barbata 98.3 Brotula multibarbata 99.5 MB51 Pleuronectes platessa Pleuronectes platessa 99.1 Pleuronectes platessa 99.5 MB52 Isurus oxyrinchus Isurus oxyrinchus 99.2 Isurus oxyrinchus 99.5 MB53 Lates niloticus Lates niloticus 98.2 Lates niloticus 97.1 MB54 Isurus oxyrinchus Isurus oxyrinchus 99.5 Isurus oxyrinchus 99.5 MB55 Mustelus mustelus Mustelus asterias 98.3 Mustelus asterias 98.3 Reinhardtius Reinhardtius MB56 Reinhardtius hippoglossoides 99.1 99.5 hippoglossoides hippoglossoides MB57 Theragra chalcogramma Theragra chalcogramma 98.7 Gadus chalcogrammus 99.4 MB58 Pleuronectes platessa Pleuronectes platessa 98.3 Pleuronectes platessa 99.1 MB59 Sebastes mentella Sebastes mentella 99.1 Sebastes viviparus 99.5 MB60 Pollachius virens Pollachius virens 99.1 Pollachius virens 100 MB61 Isurus oxyrinchus Isurus oxyrinchus 99.1 Isurus oxyrinchus 99.4 MB62 Gadus morhua Gadus morhua 99.5 Gadus morhua 99.5 MB63 Pollachius virens Pollachius virens 99.5 Pollachius virens 100 MB64 Xiphias gladius Xiphias gladius 98.8 Xiphias gladius 100 MB65 Pleuronectes platessa Pleuronectes platessa 99.1 Pleuronectes platessa 99.5 MB66 N/A N/A N/A N/A N/A MB67 Gadus morhua Gadus morhua 96.5 Gadus morhua 98.6 MB68 Mustelus mustelus Mustelus asterias 98.1 Mustelus asterias 97.5 MB69 Gadus macrocephalus N/A N/A N/A N/A MB70 Gadus morhua Gadus morhua 99.1 Gadus morhua 97.8 MB71 N/A Theragra chalcogramma 99.1 Gadus chalcogrammus 98.3 Foods 2021, 10, 1449 7 of 11

The sequencing results and their comparison with available genomic databases al- lowed the recognition and identification of various fish species present in the analyzed commercial fish products. The obtained identity scores ranged between 96.5 and 100% in BLAST and 97.1 and 100% in BOLD. Mismatches between BLAST and BOLD were appropriately corrected by integrating either result. In fact, according to the 98% threshold value for species identification [21], three samples were discharged after using BLAST but all three of them were recovered after BOLD matching. Similarly, four products displayed a low identity score using BOLD but they were recovered using BLAST. Among the 69 samples successfully attributed, a total number of eight species substitutions were detected (11.6%). In particular, four major frauds (MB19, MB25, MB38, MB44) related to mislabeling at the genus level (5.8%) and four minor (MB07, MB20, MB55, MB68) ones concerning different species within the same genus were detected (5.8%). The single names and substitutions are fully described in Table2. Among the four major frauds, two samples labeled as Katsowomus pelamis (MB19 and MB25) turned out to be either Thunnus thynnus (GenBank) or Thunnus maccoyii (BOLD). Similarly, Chelidonichtys lucerna (BAR38) was found to be Merluccius paradoxus (GenBank and BOLD), and Lamna nasus (MB44) was Ixurus oxyrinchus (GenBank and BOLD). Concerning minor frauds, the four labeled species displayed lower identity percentages in BLAST and BOLD within the same genus: MB07 (respectively 97.1% and 99.1%), MB20 (96.4% and 97.5%), MB55 (97.1% for both databases), MB68 (97.5% and 97.1%). Discrepancies between GenBank and BOLD were also evaluated and were evident in eight samples (MB07, MB19, MB20, MB25, MB37, MB49, MB50, MB59) (11.6%). Interestingly, among the eight species substitutions, application of the IUCN index [22] revealed three Critically Endangered (CR) (MB19, MB25, MB44), two Near Threatened (NT) (MB55, MB68), two Least Concern (LC) (MB07, MB20) and one Not Evaluated (MB38) species.

4. Discussion The mini-barcoding approach based on analysis of short COI fragments proved to be a useful methodology to define the correct taxonomy of commercial fish products. Among previously proposed primer sets, a choice was made based on the most reliable ones [15,17], and “Fish_miniE” showed a lower success rate than “Fish_mini”. In particular, the lower success of “Fish_miniE” (87.3%) was consistent with the one original report of 88.6% by Shokralla et al. [15], which was determined in a lower number of samples compared to our work. In fact, the authors correctly classified 39 of 44 samples, which is almost half the number of samples determined in our dataset. On the other hand, the experimental success of “Fish_mini” (97.2%) was in accordance with similar recent works (93.2%) based on longer sequences [23], and thus confirmed the reliability of the mini-barcoding methodology. Although new markers are emerging for charismatic fish species and add technological improvements to this topic [24–26], the need for data-rich databases is still important, particularly in the case of widespread investigations at a national level. From this point of view, the BOLD database is considered better performing than BLAST; however, integration of different databanks is fundamental to reaching a reliable attribution. Consistency between databases should be expected but that is not always the case. On the other hand, a correct assessment at the species level is sometimes difficult due to contradictory identity scores and variable species names released by different databases. This aspect can generate trivial attributions, particularly whenever labeling does not report the scientific name or the appropriate fishing area, as happened in a limited number of our samples. Discrepancies between GenBank and BOLD had already emerged in the past and were evaluated by Sultana et al. [17], who evidenced that BOLD records were available for only 10,000 species. This number has recently rapidly increased to over 24,000 fish species; therefore, ambiguity problems should nowadays be limited to intraspecific variability and population diversity. Although intraspecific genetic diversity should be scarce using COI, Foods 2021, 10, 1449 8 of 11

the need for a continuous update of databases is important to reach a wide coverage of different populations over a large geographic scale. In this research, the intervention of expert judgment was, therefore, necessary to evaluate genetic results that had to be integrated with sampling information useful to determine species-specific ecological characteristics (in particular, reported species name coupled to the area of origin, whenever available). To better clarify this concept, that was the case of sample MB19, which was labeled as Pacific Katsuwonus pelamis. BLAST and BOLD analyses returned two different Bluefin tuna species (Thunnus thynnus and T. maccoyii), therefore, revealing a mislabeled sample. Expert judgment was important in assigning the sample to Southern Bluefin Tuna rather than to Atlantic Bluefin Tuna according to both the identity score and the area of origin, the former species being a Pacific taxon consistent with the declared fishing zone. Similarly, sample MB38 was not properly considered a fraud but rather hypothesized as an involuntary substitution that happened during delivery at the moment of purchasing. In fact, Chelidonichtys lucerna and Merluccius paradoxus have completely different meat colors and morphologies, even after processing, in their fillet appearance. Fillets of both species were also close to each other in the exposition counter. The product was classified anyway as a major fraud since the final delivery still belongs to the entire traceability process. From a general point of view, the research evidenced 5.8% major frauds and 5.8% minor ones. Major and minor frauds were considered in relation to the taxonomic level of erroneous labeling. A final percentage of 11.6% of species substitutions were, therefore, discovered. It must be remarked that data are greatly variable on a world scale. As a matter of comparison, mislabeling was detected in 9.3% of seafood products in Germany [27], 24% in South Brazil [28] and 22% in India [29]. The results of Di Pinto et al. [30], based on molecular investigations, revealed an incredible occurrence of 82% of incorrect species declaration in fish fillet products. In some cases, the results could be biased by the product choice at the time of purchasing; this may be relevant whenever fillets are selectively chosen among suspected or evident frauds. In our investigation, fresh and frozen products were randomly bought with no particular attention to species or brands. Independent of local data, our results were in agreement with a recently published paper assuming that the most credible average mislabeling rate at the product level is 8% [31]. Besides the generalized assessment of multiple specimens, the experimental design considered a long time comparison starting from the previous work by Filonzi et al. [19] (see Figure1). Our previous study [ 19] was among the first highlighting a high occurrence of incorrect species declaration in fillet fish products, underlying the strong trend towards seafood mislabeling in the Italian retail sector [30,32–35]. The past work [19] revealed incorrect labeling in 22 of 69 samples (32%), 18 of which were serious frauds (26.1%) from both the financial and nutritional points of view. The final aim of this new investigation was undoubtedly to assess the new trend after a decade of technical innovation and market surveillance. Results have evidenced a decrease in incorrect labeling in Italy from 32 to 11.6% over the last ten to eleven years. In particular, major frauds decreased from 26.1% to 5.8%. Data were in the low end of mislabeling rates reported in the literature [23]. It is noteworthy to observe that to minimize and prevent seafood frauds, proper regulations were issued in Europe and recommended on other continents. For example, fish labeling with both common and scientific names to be included on the product label together with FAO fishing area is nowadays mandatory and has been the current practice in Italy over the last decade. Similarly, Mariani et al. [36] also observed a sudden reduction of seafood mislabeling in Europe due to recent efforts in legislation governance with a positive impact on the entire commercial chain. Compared to data reported in this interesting publication [36], our percentages are in strict agreement with those obtained in several other European countries and fill the gap concerning the lack of data about Italy. Foods 2021, 10, x FOR PEER REVIEW 9 of 11 Foods 2021, 10, 1449 9 of 11

Figure 1. Comparison of percentages of species substitutions, both as major and minor frauds, assessed in 2010 and in the Figurepresent 1. work. Comparison of percentages of species substitutions, both as major and minor frauds, assessed in 2010 and in the present work. Nonetheless, another major issue is the illegal sacrifice and trade of endangered species widely protected by an international fishing ban. Fraudulent substitutions seem Nonetheless, another major issue is the illegal sacrifice and trade of endangered to continue, particularly in sharks and tunas, despite apparently increased control since species widely protected by an international fishing ban. Fraudulent substitutions seem the first published papers focusing on the problem [19,33]. Interestingly, application of the to continue, particularly in sharks and tunas, despite apparently increased control since IUCN index [22] among eight species substitutions revealed three Critically Endangered the first published papers focusing on the problem [19,33]. Interestingly, application of (CR), two Near Threatened (NT), two Least Concern (LC) and one Not Evaluated species. theThis IUCN aspect index is also [22] related among to conservation eight species biology substitutions problems, revealed rather three thanjust Critically the food Endan- safety geredsystem, (CR and), two will Near have toThreatened be furtherly (NT monitored), two Least using Concern mini-barcoding, (LC) and eventuallyone Not Evaluated widened species.to new This genes aspect [24]. is In also this related respect to Mini-barcodingconservation biology could problems, be considered rather as than a sensitive just the foodapplication safety tool system, or applied and will to specific have to taxa be furtherlyhighlighted monitored as very often using mislabeled mini-barcoding, and as eventuallyleading to importantwidened to health new problemsgenes [24] [.37 In]. this respect Mini-barcoding could be considered as a sensitive application tool or applied to specific taxa highlighted as very often mislabeled5. Conclusions and as leading to important health problems [37]. Mini-barcoding is a valuable tool to assess seafood species substitution, particularly in 5.the Conclusions case of processed products, displaying a high success rate. Despite DNA degradation, whichMini may-barcoding limit its diagnostic is a valuable reliability, tool to assess the majority seafood of species samples substitution, were correctly particularly classified inusing the case BOLD of andprocessed BLAST products, databases displaying when supported a high success by expert rate. evaluation Despite DNA to solve degrada- cryptic tionnomenclature, which may cases limit or its apparent diagnostic database reliability, redundancies. the majority Although of sampl a generales were decreasing correctly classifiedtrend in fish using species BOLD substitutions and BLAST over databases the last decade when wassupported observed, by consistent expert evaluation with similar to solvetrends cryptic in other nomenclature European countries, cases or aapparent continuous database update redundancies. of datasets is importantAlthough toa general reach a decreasingwide coverage trend of differentin fish species species substitutions and populations. over In the particular, last decade special was attention observed should, con- sistentbe focused with onsimilar critically trends endangered in other European species sensu countries,IUCN a whose continuous involvement update in of mislabeling datasets is importantis recurrent to and reach suggests a wide still coverage existing of inappropriate different species control and processes populations. at different In particular, levels. special attention should be focused on critically endangered species sensu IUCN whose involvementAuthor Contributions: in mislabelingL.F. was is involved recurrent in theand conceptualization, suggests still existing analysis, inappropriate data collection, control supervi- processession and writing at different of the originallevels. draft. M.V. and A.A. were involved in the data collection, analysis and data elaboration. A.V. and P.M.R. were involved in the data and sample collection. F.N.M. contributed through conceptualization, supervision, project administration and review and editing Author Contributions: L.F. was involved in the conceptualization, analysis, data collection, su- of the writing. All authors have read and agreed to the published version of the manuscript. pervision and writing of the original draft. M.V. and A.A. were involved in the data collection, analysisFunding: andThis data research elaboration. was partly A.V. developed and P.M. withR. were local involved funding in by the the data University and sample of Parma—Grant collection. F.N.M.FIL2020—and contributed with through the financial conceptualization, support of Spin supervision, Off Gen-Tech project S.r.l. administration and review and editing of the writing. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement: Ethical review and approval were not necessary for this study Funding:since it did This not involve research humans was partlyor alive developed animals. All with products local were funding purchased by the already University processed. of Par- ma—Grant FIL2020—and with the financial support of Spin Off Gen-Tech S.r.l. Acknowledgments: The work has benefited from the equipment and framework of the COMP-HUB InstitutionalInitiative, funded Review by theBoard ‘Departments Statement: of Ethical Excellence’ review program and approval of the Italian were Ministrynot necessary for Education, for this studyUniversity since andit did Research not involve (MIUR, humans 2018–2022). or alive animals. All products were purchased already processed. Conflicts of Interest: The authors declare no conflict of interest.

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